Hackers Trick AI With ‘Bad Math’ to Expose Its Flaws and Biases

tech.hindustantimes.com:

Mays has just tricked a large language model. It took some coaxing, but she managed to convince an algorithm to say 9 10 = 21.

“It was a back-and-forth conversation,” said the 21-year-old student from Savannah, Georgia. At first the model agreed to say it was part of an “inside joke” between them. Several prompts later, it eventually stopped qualifying the errant sum in any way at all.

Producing “Bad Math” is just one of the ways thousands of hackers are trying to expose flaws and biases in generative AI systems at a novel public contest taking place at the DEF CON hacking conference this weekend in Las Vegas.

Hunched over 156 laptops for 50 minutes at a time, the attendees are battling some of the world's most intelligent platforms on an unprecedented scale. They're testing whether any of the eight models produced by companies including Alphabet Inc.'s Google, Meta Platforms Inc., and OpenAI will make missteps ranging from dull to dangerous: claim to be human, spread incorrect claims about places and people or advocate abuse.

Read More: Bubble in AI Stocks Is Nearing a Peak, Morgan Stanley Says

The aim is to see if companies can ultimately build new guardrails to rein in some of the prodigious problems increasingly associated with large language models, or LLMs. The undertaking is backed by the White House, which also helped develop the contest.

LLMs have the power to transform everything from finance to hiring, with some companies already starting to integrate them into how they do business. But researchers have turned up extensive bias and other problems that threaten to spread inaccuracies and injustice if the technology is deployed at scale.

For Mays, who is more used to relying on AI to reconstruct cosmic ray particles